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ISSN 2083-6473
ISSN 2083-6481 (electronic version)
 

 

 

Editor-in-Chief

Associate Editor
Prof. Tomasz Neumann
 

Published by
TransNav, Faculty of Navigation
Gdynia Maritime University
3, John Paul II Avenue
81-345 Gdynia, POLAND
www http://www.transnav.eu
e-mail transnav@umg.edu.pl
GNSS Positioning Error Change-point Detection in GNSS Positioning Performance Modelling
1 University of Ljubljana, Ljubljana, Slovenia
2 Zagreb University of Applied Sciences, Zagreb, Croatia
3 University of Rijeka, Rijeka, Croatia
Times cited (SCOPUS): 3
ABSTRACT: Provision of uninterrupted and robust Positioning, Navigation, and Timing (PNT) services is essential task of Global Navigation Satellite Systems (GNSS) as an enabling technology for numerous technology and socio-economic applications, a cornerstone of the modern civilisation, a public goods, and an essential component of a national infrastructure. GNSS resilience may be accomplished only with complete understanding of the causes of GNSS positioning performance disruptions and degradations, presented in a form of applications- and scenarios-related models. Here the application of change-point detection methods is proposed and demonstrated in a selected scenario of a fast-developing ionospheric storm’s impact on GNSS positioning performance, as a novel contribution to forecasting GNSS positioning performance model development and GNSS utilisation risk mitigation.
REFERENCES
Aminikhanghahi, S, Cook, D. (2017). A Survey of methods for time series change point detection. Knowledge and Information Systems, 51(2), 339-367. Available at: https://www.eecs.wsu.edu/~cook/pubs/kais16.2.pdf - doi:10.1007/s10115-016-0987-z
Chandola, V, Vatsavai, R R. (2011). A Gaussian Process Based Online Change Detection Algorithm for Monitoring Periodic Time Series. Proc of the 2011 SIAM International Conference on Data Mining, 95-106. Mesa, AZ. - doi:10.1137/1.9781611972818.9
Filić, M, Filjar, R. (2019). On correlation between SID monitor and GPS-derived TEC observations during a massive ionospheric storm development. Best Student Paper Award at URSI AP-RASC 2019. New Delhi, India. Available at: https://bit.ly/2FSJu0Y - doi:10.23919/URSIAP-RASC.2019.8738664
Filić, M, Filjar, R. (2018). Forecasting model of space weather-driven GNSS positioning performance. Lambert Academic Publishing. Riga, Latvia. ISBN 978-613-9-90118-0.
Gustafsson, F. (2000). Adaptive Filtering and Change Detection. John Wiley & Sons. Chichester, UK. - doi:10.1002/0470841613
Killick, R. (2016). R Package changepoint. R project for statistical computing. Available at: https://cran.r-project.org/web/packages/changepoint/index.html
Killick, R, Eckley, I A. (2014). Changepoint: An R Package for Changepoint Analysis. Journal of Statistical Software, 58(39, 1-19. doi: 10.18637/jss.v058.i03 - doi:10.18637/jss.v058.i03
Lenac, K, Filić, M, Filjar, R. (2019). GPS ionospheric delay dynamics characterisation using recurrence plot analysis. Presented for consideration to J of Navigation (Cambridge University Press).
NOAA. (2019). Kp index data archive. US National Oceanic and Atmospheric Administration (NOAA). Available at: ftp://ftp.swpc.noaa.gov/pub/indices/old_indices/
Sonel. (2019). Internet archive of GPS observations. SONEL network. Available at: https://www.sonel.org
Schroeder, A L M M. (2016). Methods for Change-Point Detection with Additional Interpretability. London School of Economics and Political Sciences. London, UK. Available at: http://etheses.lse.ac.uk/3421/
Scott, A J, Knott, M. (1974). A Cluster Analysis Method for Grouping Means in the Analysis of Variance. Biometrics, 30(3), 507-512. - doi:10.2307/2529204
Truong, C, Oudre, L, Vaytis, N. (2019). Selective review of offline change point detection methods. Preprint at arXiv: 1801.00718. Available at: https://arxiv.org/pdf/1801.00718.pdf
Watanabe, S. (2013). A Widely Applicable Bayesian Information Criterion. J of Machine Learning Res, 14, 867-897. Available at: http://www.jmlr.org/papers/volume14/watanabe13a/watanabe13a.pdf
HM Government Office for Science. (2018). Satellite-Derived Time and Position: A Study of Critical Dependencies. HM Government of the United Kingdom and Northern Ireland. Available at: https://bit.ly/2E2STnd
Citation note:
Filić M., Filjar R.: GNSS Positioning Error Change-point Detection in GNSS Positioning Performance Modelling. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, Vol. 13, No. 3, doi:10.12716/1001.13.03.12, pp. 575-579, 2019
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